Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
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Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. ⋯ Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.
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To determine how often emergency physicians (EPs) scanning the abdominal aorta (AA) of nonfasted emergency department (ED) patients are able to visualize the entire AA. ⋯ Significant portions of AA (at least one third of its length) were not visualized on bedside US in 8% of nonfasted patients; this rate is higher than radiology studies of fasted patients receiving US for evaluation of their aortas.
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Many people die in emergency departments (EDs) across the United States from sudden illnesses or injuries, an exacerbation of a chronic disease, or a terminal illness. Frequently, patients and families come to the ED seeking lifesaving or life-prolonging treatment. In addition, the ED is a place of transition-patients usually are transferred to an inpatient unit, transferred to another hospital, or discharged home. ⋯ However, these end-of-life care models are based on chronic disease trajectories and have difficulty accommodating sudden-death trajectories common in the ED. There is very little information about end-of-life care in the ED. This article explores ED culture and characteristics, and examines the applicability of current end-of-life care models.